Abstract
Electrocardiogram (ECG) is a quasi-periodic rhythmic signal harmonized with the activity of the heart. Investigation of the electrocardiogram (ECG) signals has turned into an emergent procedure for diagnosing cardiac arrhythmias. Since ECGs are low level signals and frequently contaminated by noise which inclines to change the morphology of the signal, the accurate diagnosis is drastically hampered. This research proposes a fuzzy filtering method based on the adaptable window to eliminate the noise. The efficacy of the proposed approach has been validated over experiments to compare with the commonly employed signal error calculation measures like Signal to noise ratio (SNR), Root Mean Square (RMS) error, and Maximum Amplitude (MAX) error.